A Semi-Empirical Model to Predict Diesel Engine Combustion Parameters

Authors

  • B. Ghobadian Tarbiat Modares University, Tehran, Iran
  • G. Najafi Tarbiat Modares University, Tehran, Iran
  • M. Nayebi Tarbiat Modares University, Tehran, Iran

DOI:

https://doi.org/10.15282/jmes.4.2013.2.0035

Keywords:

cylinder pressure model; parameters of engine; diesel engine

Abstract

To carry out the investigation, a cylinder pressure model was developed based on the position of the crankshaft, engine load, engine speed, and fuel injection time. This model takes into account the maximum number of parameters involved. The accuracy of the model was verified by experimental results. The average error of the cylinder pressure, the average radical of the square of the error of the cylinder pressure, and the average error of maximum pressure were calculated at 1.85%, 3.32, and 0.66% (of maximum pressure), respectively. This model was compared with the model by Conolly and Yagle; the two models are similar in terms of the pressure relating the square of time and the exponential of time. This model appears applicable to other diesel engines. The results of the equation and experimental results were compared and described by a Fourier series, which is indicative of the cylinder pressure level between them.

References

Abbaszaadeh, A., Ghobadian, B., Omidkhah, M. R., & Najafi, G. (2012). Current biodiesel production technologies: A comparative review. Energy Conversion and Management, 63, 138–148.

Aggarwal, K. M. (1995). Automobile design program. Delhi: Satya publisher.

Amana, C. A. (1974). Why the piston engine lives on. Machine Design, 46, 1-5.

Azad, A. K., Ameer Uddin, S. M., & Alam, M. M. (2012). A comprehensive study of DI diesel engine performance with vegetable oil: an alternative boi-fuel source of energy. International Journal of Automotive and Mechanical Engineering, 5, 576-586.

Aziz, A. R. A., Firmansyah, & Shahzad, R. (2010). Combustion analysis of a CNG direct injection spark ignition engine. International Journal of Automotive and Mechanical Engineering, 2, 156-170.

Connoly, F. T., & Yaggle, A. E. (1993). Modeling and identification of the combustion pressure process in internal combustion engines. Journal of Engineering for Gas Turbines. 115, 65-75.

Farrauto, R. J., & Voss, K. E. (1996). Monolithic Diesel oxidation catalysts. Applied Catalysis B: Environmental, 10, 29-51.

Ghobadian, B., Rahimi, H., Nikbakht, A. M., Najafi, G., & Yusaf, T. F. (2009). Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network. Renewable Energy, 34, 976–982.

Heywood, J. B. (1988). Internal combustion engine fundamentals. New York: McGraw-Hill.

Kiani Deh Kiani, M., Ghobadian, B., Tavakoli, T., Nikbakht, A. M., & Najafi, G. (2010). Application of artificial neural networks for the prediction of performance. Energy, 35, 65–69.

Kopa, R. D., & Kimura, H. (1960). Exhaust gas recirculation as a method of nitrogen oxides control in an internal combustion engine. APCA 53rd Annual Meeting, Cincinnati, Ohio, USA.

Ladommatos, N., Abdelhalim, S. M., Zhao, H., & Hu, Z. (1996). The dilution, chemical, and thermal effects of exhaust gas recirculation on diesel engine emissions. SAE Paper No. 961165.

Lee, C. S., & Choi, N. J. (1991). A study on the variations of combustion characteristics in diesel engine. SAE Paper No. 911245.

Mogi, H., Tajima, K., Hosoya, M., & Shimoda, M. (1999). The reduction of diesel engine emission by using the oxidation catalysts on Japan Diesel 13 mode cycle. SAE Paper No. 1999-01-047.

Mozafary, A. (1994). Exhaust gas recirculation in spark ignition engine. Advanced Heat Transfer ASME, 64(1), 197-202.

Najafi, G., Ghobadian, B., Tavakoli, T., Buttsworth, D. R., Yusaf, T. F., & Faizollahnejad, M. (2009). Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network. Applied Energy, 86, 630–639.

Nematizade, P., Ghobadian, B., & Najafi, G. (2012). Investigation of fossile fuel and liquid biofuel blend properties using arteficial neural network. International Journal of Automotive and Mechanical Engineering, 5, 639-647.

Pedersen, P.S., & Qwale, B. (1974). A model for the physical part of the ignition delay in a diesel engine. SAE Paper No. 740716.

Rahim, R., Mamat, R., Taib, M. Y., & Abdullah, A. A. (2012). Influence of fuel temperature on a diesel engine performance operating with biodiesel blended. Journal of Mechanical Engineering and Sciences, 2, 226.236.

Rahimi, H. Ghobadian, B., Yusaf, T., Najafi, G., & Khatamifar, M. (2009). Diesterol: An environment-friendly IC engine fuel. Renewable Energy, 34, 335–342.

Smit, H., & Fox, M. M. (1955(. Automobile exhaust and ozone formation. SAE Golden Anniversary Meeting, Detroid, Michigan, USA.

Yee, S. Y., & Linville, W. (1960). The effect of exhaust gas recirculation on oxides of nitrogen. APCA 53rd Annual Meeting, Cincinnati, Ohio, USA.

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Published

2013-06-30

How to Cite

[1]
B. Ghobadian, G. Najafi, and M. Nayebi, “A Semi-Empirical Model to Predict Diesel Engine Combustion Parameters”, J. Mech. Eng. Sci., vol. 4, no. 1, pp. 373–382, Jun. 2013.

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